{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Minimization.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "tYUUT2SvD6B3"
      ],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/google/jax-md/blob/master/notebooks/minimization.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kNDQ02qlDnNW",
        "cellView": "form"
      },
      "source": [
        "#@title Imports & Utils\n",
        "\n",
        "!pip install jax-md\n",
        "\n",
        "import numpy as onp\n",
        "\n",
        "import jax.numpy as np\n",
        "from jax.config import config\n",
        "config.update('jax_enable_x64', True)\n",
        "\n",
        "from jax import random\n",
        "from jax import jit\n",
        "\n",
        "from jax_md import space, smap, energy, minimize, quantity, simulate\n",
        "from jax_md.colab_tools import renderer\n",
        "\n",
        "import matplotlib\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "  \n",
        "sns.set_style(style='white')\n",
        "\n",
        "def format_plot(x, y):  \n",
        "  plt.grid(True)\n",
        "  plt.xlabel(x, fontsize=20)\n",
        "  plt.ylabel(y, fontsize=20)\n",
        "  \n",
        "def finalize_plot(shape=(1, 1)):\n",
        "  plt.gcf().set_size_inches(\n",
        "    shape[0] * 1.5 * plt.gcf().get_size_inches()[1], \n",
        "    shape[1] * 1.5 * plt.gcf().get_size_inches()[1])\n",
        "  plt.tight_layout()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uxCDg0ioWh70"
      },
      "source": [
        "# Harmonic Minimization"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dFK0Dew5MwXt"
      },
      "source": [
        "Here we demonstrate some simple example code showing how we might find the inherent structure for some initially random configuration of particles. Note that this code will work on CPU, GPU, or TPU out of the box.\n",
        "\n",
        "First thing we need to do is set some parameters that define our simulation, including what kind of box we're using (specified using a metric function and a wrapping function)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yGdrjCj1Wm9J"
      },
      "source": [
        "N = 1000\n",
        "dimension = 2\n",
        "box_size = quantity.box_size_at_number_density(N, 0.8, dimension)\n",
        "displacement, shift = space.periodic(box_size) "
      ],
      "execution_count": 58,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uFrxHj12M3X1"
      },
      "source": [
        "Next we need to generate some random positions as well as particle sizes."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fRHuSTD1eZBx"
      },
      "source": [
        "key = random.PRNGKey(0)"
      ],
      "execution_count": 59,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5ApXCCgdWm9O"
      },
      "source": [
        "R = box_size * random.uniform(key, (N, dimension), dtype=np.float32)\n",
        "\n",
        "# The system ought to be a 50:50 mixture of two types of particles, one\n",
        "# large and one small.\n",
        "sigma = np.array([[1.0, 1.2], [1.2, 1.4]])\n",
        "N_2 = int(N / 2)\n",
        "species = np.where(np.arange(N) < N_2, 0, 1)"
      ],
      "execution_count": 60,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hjPUEPcwM6jc"
      },
      "source": [
        "Then we need to construct our FIRE minimization function. Like all simulations in JAX MD, the FIRE optimizer is two functions: an `init_fn` that creates the state of the optimizer and an `apply_fn` that updates the state to a new state."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B1xXV_FmWm9Q"
      },
      "source": [
        "energy_fn = energy.soft_sphere_pair(displacement, species=species, sigma=sigma)\n",
        "fire_init, fire_apply = minimize.fire_descent(energy_fn, shift)\n",
        "fire_apply = jit(fire_apply)\n",
        "fire_state = fire_init(R)"
      ],
      "execution_count": 61,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hJRvIrfiNAgV"
      },
      "source": [
        "Now let's actually do minimization, keepting track of the energy and particle positions as we go."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "psqU1uEPWm9T"
      },
      "source": [
        "E = []\n",
        "trajectory = []\n",
        "\n",
        "for i in range(200):\n",
        "  fire_state = fire_apply(fire_state)\n",
        "  \n",
        "  E += [energy_fn(fire_state.position)]\n",
        "  trajectory += [fire_state.position]\n",
        "  \n",
        "R = fire_state.position\n",
        "trajectory = np.stack(trajectory)"
      ],
      "execution_count": 62,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0hhEEuojNFht"
      },
      "source": [
        "Let's plot the nearest distance for different species pairs. We see that particles on average have neighbors that are the right distance apart."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jiJOwCAPirFn",
        "outputId": "b169edfd-237f-4b6c-c3bd-366d414dd26e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        }
      },
      "source": [
        "metric = lambda R: space.distance(space.map_product(displacement)(R, R))\n",
        "dr = metric(R)\n",
        "plt.plot(np.min(dr[:N_2, :N_2] + 5 * np.eye(N_2, N_2), axis=0), 'o', \n",
        "         label='$\\\\sigma_{AA}$')\n",
        "plt.plot(np.min(dr[:N_2, N_2:] + 5 * np.eye(N_2, N_2), axis=0), 'o',\n",
        "         label='$\\\\sigma_{AB}$')\n",
        "plt.plot(np.min(dr[N_2:, N_2:] + 5 * np.eye(N_2, N_2), axis=0), 'o',\n",
        "         label='$\\\\sigma_{BB}$')\n",
        "\n",
        "plt.legend()\n",
        "format_plot('', 'min neighbor distance')\n",
        "finalize_plot()"
      ],
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4428Kz16NP4O"
      },
      "source": [
        "Now let's plot the system. It's nice and minimized!"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qhx3-RTWWm9Y",
        "outputId": "3c844066-d491-4cd8-8d74-da82d39950e9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 873
        }
      },
      "source": [
        "ms = 45\n",
        "R_plt = onp.array(fire_state.position)\n",
        "\n",
        "plt.plot(R_plt[:N_2, 0], R_plt[:N_2, 1], 'o', markersize=ms * 0.5)\n",
        "plt.plot(R_plt[N_2:, 0], R_plt[N_2:, 1], 'o', markersize=ms * 0.7)\n",
        "\n",
        "plt.xlim([0, np.max(R[:, 0])])\n",
        "plt.ylim([0, np.max(R[:, 1])])\n",
        "\n",
        "plt.axis('off')\n",
        "\n",
        "finalize_plot((2, 2))"
      ],
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x864 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uMjvXzgS2qvn"
      },
      "source": [
        "If we want, we can visualize the entire minimization."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L2hLGadF3DpR",
        "outputId": "02abd351-46af-47d8-afe2-54fb0edfd962",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1246
        }
      },
      "source": [
        "diameter = np.where(species, 1.4, 1.0)\n",
        "color = np.where(species[:, None], \n",
        "                 np.array([[1.0, 0.5, 0.05]]), \n",
        "                 np.array([[0.15, 0.45, 0.8]]))\n",
        "renderer.render(box_size, \n",
        "                { 'particles': renderer.Disk(trajectory, diameter, color)},\n",
        "                buffer_size=50)"
      ],
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<!--\n",
              "  Copyright 2020 Google LLC\n",
              "  Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "  you may not use this file except in compliance with the License.\n",
              "  You may obtain a copy of the License at\n",
              "      https://www.apache.org/licenses/LICENSE-2.0\n",
              "  Unless required by applicable law or agreed to in writing, software\n",
              "  distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "  See the License for the specific language governing permissions and\n",
              "  limitations under the License.\n",
              "-->\n",
              "\n",
              "<!--\n",
              "  A fragment of HTML and Javascript that describes a visualization tool.\n",
              "  \n",
              "  This code is expected to be injected into Jupyter or Colaboratory notebooks using the `IPython.display.HTML` function. The tool is rendered using WebGL2.\n",
              "-->\n",
              "\n",
              "<div id='seek'>\n",
              "  <button type='button'\n",
              "          id='pause_play' \n",
              "          style='width:40px; vertical-align:middle;' \n",
              "          onclick=\"toggle_play()\"> || \n",
              "  </button>\n",
              "  <input type=\"range\" \n",
              "         min=\"0\"\n",
              "         max=\"1\"\n",
              "         value=\"0\"\n",
              "         style=\"width:512px; vertical-align:middle;\"\n",
              "         class=\"slider\"\n",
              "         id=\"frame_range\"\n",
              "         oninput='change_frame(this.value)'>\n",
              "</div>\n",
              "<canvas id=\"canvas\"></canvas>\n",
              "<div id='info'> </div>\n",
              "<div id='error' style=\"color:red\"> </div>\n",
              "<script src=\"https://cdnjs.cloudflare.com/ajax/libs/gl-matrix/2.8.1/gl-matrix-min.js\"></script>\n",
              "\n",
              "<script>\n",
              "  var DIMENSION;\n",
              "\n",
              "  var SIZE;\n",
              "\n",
              "  var SHAPE = {};\n",
              "\n",
              "  var GEOMETRY = {};\n",
              "\n",
              "  var CURRENT_FRAME = 0;\n",
              "  var FRAME_COUNT = 0;\n",
              "\n",
              "  var BOX_SIZE;\n",
              "  var READ_BUFFER_SIZE = null;\n",
              "  var IS_LOADED = false;\n",
              "  var SIMULATION_IDX = 0;\n",
              "\n",
              "  // Info\n",
              "\n",
              "  var INFO = document.getElementById('info');\n",
              "  var ERROR = document.getElementById('error');\n",
              "\n",
              "  // Graphics\n",
              "\n",
              "  var GL;\n",
              "  var SHADER;\n",
              "  var BACKGROUND_COLOR = [0.2, 0.2, 0.2];\n",
              "\n",
              "  // 3D Camera\n",
              "\n",
              "  var EYE = mat4.create();\n",
              "  var PERSPECTIVE = mat4.create();\n",
              "  var LOOK_AT = mat4.create()\n",
              "  var YAW = 0.0;\n",
              "  var PITCH = 0.0;\n",
              "  var CAMERA_POSITION = mat4.create();\n",
              "  var Y_ROTATION_MATRIX = mat4.create();\n",
              "  var X_ROTATION_MATRIX = mat4.create();\n",
              "  var VIEW_DISTANCE = 0.0;\n",
              "\n",
              "  function make_look_at() {\n",
              "    var center = [BOX_SIZE[0] / 2.0, BOX_SIZE[1] / 2.0, BOX_SIZE[2] / 2.0];\n",
              "    var direction = [Math.cos(YAW) * Math.cos(PITCH),\n",
              "                     Math.sin(PITCH),\n",
              "                     Math.sin(YAW) * Math.cos(PITCH)];\n",
              "    var pos = [center[0] - VIEW_DISTANCE * direction[0],\n",
              "               center[1] - VIEW_DISTANCE * direction[1],\n",
              "               center[2] - VIEW_DISTANCE * direction[2]];\n",
              "    mat4.lookAt(LOOK_AT, \n",
              "                pos, \n",
              "                center, \n",
              "                [0.0, 1.0, 0.0]);\n",
              "  }\n",
              "\n",
              "  // 2D Camera\n",
              "\n",
              "  var SCREEN_POSITION = [0, 0];\n",
              "  var CAMERA_SIZE = [0, 0];\n",
              "\n",
              "  // Bonds\n",
              "\n",
              "  const BOND_SEGMENTS = 3;\n",
              "  const VERTICES_PER_BOND = BOND_SEGMENTS * 6;\n",
              "\n",
              "  // Simulation State\n",
              "\n",
              "  var IS_PLAYING = true;\n",
              "  var PLAY_PAUSE_BUTTON = document.getElementById('pause_play');\n",
              "\n",
              "  var FRAME_RANGE = document.getElementById('frame_range');\n",
              "\n",
              "  google.colab.output.setIframeHeight(0, true, {maxHeight: 5000});\n",
              "  var invokeFunction = google.colab.kernel.invokeFunction;\n",
              "\n",
              "  var CANVAS = document.getElementById(\"canvas\");\n",
              "  CANVAS.width = 1024;\n",
              "  CANVAS.height = 1024;\n",
              "\n",
              "  // Simulation Loading.\n",
              "\n",
              "  function make_sizes() {\n",
              "    return {\n",
              "      position: DIMENSION,\n",
              "      angle: DIMENSION - 1,\n",
              "      size: 1,\n",
              "      color: 3,\n",
              "    };\n",
              "  }\n",
              "\n",
              "  function simulation_info_string() {\n",
              "    return ('<p style=\"color:yellow\">' +\n",
              "            'Simulation Info:</p><div style=\"padding-left: 20px; padding-bottom: 10px;\">' +\n",
              "            'Box Size:    ' + BOX_SIZE.map(x => parseFloat(x).toFixed(2)) + '<br>' +\n",
              "            'Dimension:   ' + DIMENSION + '<br>' +\n",
              "            'Frame Count: ' + FRAME_COUNT + '<br></div>');\n",
              "  }\n",
              "\n",
              "  async function load_simulation() {\n",
              "    console.log(\"Loading simulation.\"); \n",
              "    INFO.innerHTML = 'Loading simulation...<br>';\n",
              "\n",
              "    var result = await invokeFunction('GetSimulationMetadata', [], {});\n",
              "    var metadata = from_json(result);\n",
              "\n",
              "    if(!metadata.box_size) {\n",
              "      ERROR.innerHTML += 'ERROR: No box size specified.<br>';\n",
              "    }\n",
              "\n",
              "    FRAME_COUNT = metadata.frame_count;\n",
              "    BOX_SIZE = metadata.box_size;\n",
              "    DIMENSION = metadata.dimension;\n",
              "    SIMULATION_IDX = metadata.simulation_idx;\n",
              "\n",
              "    if (metadata.background_color)\n",
              "      BACKGROUND_COLOR = metadata.background_color;\n",
              "\n",
              "    if (metadata.resolution) {\n",
              "      CANVAS.width = metadata.resolution[0];\n",
              "      CANVAS.height = metadata.resolution[1];\n",
              "    }\n",
              "\n",
              "    const aspect_ratio = CANVAS.width / CANVAS.height;\n",
              "\n",
              "    INFO.innerHTML += simulation_info_string();\n",
              "\n",
              "    SIZE = make_sizes();\n",
              "    initialize_gl();\n",
              "\n",
              "    if (DIMENSION == 2) {\n",
              "      SCREEN_POSITION = [BOX_SIZE[0] / 2.0, BOX_SIZE[1] / 2.0];\n",
              "      CAMERA_SIZE = [aspect_ratio * BOX_SIZE[0] / 2.0, BOX_SIZE[1] / 2.0];\n",
              "    } else if (DIMENSION == 3) {\n",
              "      const fovy = 45.0 / 180.0 * Math.PI;\n",
              "      const max_box_size = Math.max(BOX_SIZE[0], BOX_SIZE[1], BOX_SIZE[2]);\n",
              "      PERSPECTIVE = mat4.perspective(PERSPECTIVE, \n",
              "                                     fovy,            // Field of view.\n",
              "                                     aspect_ratio,    // Aspect ratio.\n",
              "                                     max_box_size / 10.0, // Near clip plane.\n",
              "                                     100 * max_box_size); // Far clip plane.\n",
              "      VIEW_DISTANCE = 2 * max_box_size;\n",
              "      make_look_at();\n",
              "    } else {\n",
              "      ERROR.innerHTML += 'ERROR: Invalid dimension specified: ' + DIMENSION + '.<br>';\n",
              "    }\n",
              "\n",
              "    FRAME_RANGE.max = FRAME_COUNT - 1;\n",
              "\n",
              "    // This specifies the maximum number of frames of data we will try to\n",
              "    // transfer between Python and Javascript at a time.\n",
              "    READ_BUFFER_SIZE = metadata.buffer_size;\n",
              "    if (!READ_BUFFER_SIZE)\n",
              "      READ_BUFFER_SIZE = FRAME_COUNT;\n",
              "\n",
              "    var geometry_list = metadata.geometry;\n",
              "    if (geometry_list) {\n",
              "      for (var i = 0; i < geometry_list.length ; i++) {\n",
              "        const name = geometry_list[i];\n",
              "        GEOMETRY[name] = await load_geometry(name);\n",
              "      }\n",
              "    }\n",
              "\n",
              "    IS_LOADED = true;\n",
              "  }\n",
              "\n",
              "  async function load_geometry(name) {\n",
              "    console.log('Loading ' + name + '.');\n",
              "    INFO.innerHTML += 'Loading geometry \"' + name + '\".<br>';\n",
              "    var result = await invokeFunction('GetGeometryMetadata' + SIMULATION_IDX,\n",
              "                                      [name], {});\n",
              "    var data = from_json(result);\n",
              "\n",
              "    console.log(data);\n",
              "\n",
              "    var geometry = {};\n",
              "    geometry.name = name;\n",
              "    geometry.shape = data.shape;\n",
              "    geometry.count = data.count;\n",
              "    geometry.selected = new Int32Array(data.count);\n",
              "\n",
              "    if (data.reference_geometry)\n",
              "      geometry.reference_geometry = data.reference_geometry;\n",
              "\n",
              "    if (data.max_neighbors)\n",
              "      geometry.max_neighbors = data.max_neighbors;\n",
              "\n",
              "    if(!geometry.shape) {\n",
              "      ERROR.innerHTML += 'ERROR: No shape specified for the geometry.<br>';\n",
              "    }\n",
              "\n",
              "    for (var field in data.fields) {\n",
              "      var array;\n",
              "      var array_type;\n",
              "      if (data.fields[field] == 'dynamic') {\n",
              "        array = await load_dynamic_array(name, field, geometry.count);\n",
              "        array_type = GL.DYNAMIC_DRAW;\n",
              "      } else if (data.fields[field] == 'static') {\n",
              "        array = await load_array(name, field);\n",
              "        array_type = GL.STATIC_DRAW;\n",
              "      } else if (data.fields[field] == 'global') {\n",
              "        array = await load_array(name, field);\n",
              "        array_type = 'GLOBAL';\n",
              "      } else {\n",
              "        ERROR.innerHTML += ('ERROR: field must have type \"dynamic\", \"static\", or ' +\n",
              "                            '\"global\". Found' + data.fields[field] + '.<br>');\n",
              "      }\n",
              "\n",
              "      geometry[field] = array;\n",
              "      geometry[field + '_type'] = array_type; \n",
              "\n",
              "      if (data.shape == 'Bond' && field == 'neighbor_idx')\n",
              "        continue;\n",
              "\n",
              "      if (array_type != 'GLOBAL') {\n",
              "        var array_buffer = GL.createBuffer();\n",
              "        var array_buffer_size = 4 * SIZE[field] * geometry.count;\n",
              "        GL.bindBuffer(GL.ARRAY_BUFFER, array_buffer);\n",
              "        GL.bufferData(GL.ARRAY_BUFFER, array, array_type);\n",
              "        geometry[field + '_buffer'] = array_buffer;  \n",
              "        geometry[field + '_buffer_size'] = array_buffer_size;   \n",
              "      }\n",
              "    }\n",
              "\n",
              "    if (data.shape == 'Bond') {\n",
              "      var vertex_buffer = GL.createBuffer();\n",
              "      var vertex_count = (geometry.count * \n",
              "                          geometry.max_neighbors * \n",
              "                          VERTICES_PER_BOND);\n",
              "      var vertex_buffer_size = 4 * SIZE['position'] * vertex_count;\n",
              "      GL.bindBuffer(GL.ARRAY_BUFFER, vertex_buffer);\n",
              "      GL.bufferData(GL.ARRAY_BUFFER, vertex_buffer_size, GL.DYNAMIC_DRAW);\n",
              "\n",
              "      geometry.vertices = new Float32Array(SIZE['position'] * vertex_count);\n",
              "      geometry.vertex_buffer = vertex_buffer;\n",
              "      geometry.vertex_buffer_size = vertex_buffer_size;\n",
              "\n",
              "      var vertex_normal_buffer = GL.createBuffer();\n",
              "      GL.bindBuffer(GL.ARRAY_BUFFER, vertex_normal_buffer);\n",
              "      GL.bufferData(GL.ARRAY_BUFFER, vertex_buffer_size, GL.DYNAMIC_DRAW);\n",
              "\n",
              "      geometry.normals = new Float32Array(SIZE['position'] * vertex_count);\n",
              "      geometry.vertex_normal_buffer = vertex_normal_buffer;\n",
              "    }\n",
              "\n",
              "    return geometry;\n",
              "  }\n",
              "\n",
              "  async function load_dynamic_array(name, field, count) {\n",
              "    if (!FRAME_COUNT) {\n",
              "      ERROR.innerHTML += 'ERROR: No frame count specified.<br>';\n",
              "    }\n",
              "\n",
              "    var array = new Float32Array(FRAME_COUNT * count * SIZE[field]);\n",
              "\n",
              "    const info_text = INFO.innerHTML;\n",
              "\n",
              "    for (var i = 0 ; i < FRAME_COUNT ; i += READ_BUFFER_SIZE) {\n",
              "      await load_array_chunk(name, field, count, array, i, info_text);\n",
              "    }\n",
              "\n",
              "    INFO.innerHTML = info_text + 'Loaded \"' + field + '\".<br>';\n",
              "\n",
              "    return array;\n",
              "  }\n",
              "\n",
              "  async function load_array_chunk(name, field, count, array, offset, info_text) {\n",
              "    var dbg_string = ('Loading \"' + field + '\" chunk at time offset ' + offset +\n",
              "                      '.<br>'); \n",
              "    console.log(dbg_string);\n",
              "    INFO.innerHTML = info_text + dbg_string + '<br>';\n",
              "\n",
              "    var result = await invokeFunction('GetArrayChunk' + SIMULATION_IDX, \n",
              "                                      [name, field, offset, READ_BUFFER_SIZE],\n",
              "                                      {});\n",
              "    var data = from_json(result);\n",
              "\n",
              "    if (!data.array_chunk) {\n",
              "      // Error checking.\n",
              "    }\n",
              "\n",
              "    var array_chunk = decode(data.array_chunk);\n",
              "    array.set(array_chunk, offset * count * SIZE[field]);\n",
              "  }\n",
              "\n",
              "  async function load_array(name, field) {\n",
              "    const info_text = INFO.innerHTML;\n",
              "    INFO.innerHTML += 'Loading \"' + field + '\".<br>';\n",
              "    var result = await invokeFunction('GetArray' + SIMULATION_IDX,\n",
              "                                      [name, field], {});\n",
              "    var data = from_json(result);\n",
              "\n",
              "    if (!data.array) {\n",
              "      ERROR.innerHTML += 'ERROR: No data array specified.<br>';\n",
              "    }\n",
              "    INFO.innerHTML = info_text + 'Loaded \"' + field + '\".<br>';\n",
              "    return decode(data.array);\n",
              "  }\n",
              "\n",
              "  function initialize_gl() {\n",
              "    GL = CANVAS.getContext(\"webgl2\");\n",
              "\n",
              "    if (!GL) {\n",
              "        alert('Unable to initialize WebGL.');\n",
              "        return;\n",
              "    }\n",
              "\n",
              "    GL.viewport(0, 0, GL.drawingBufferWidth, GL.drawingBufferHeight);\n",
              "\n",
              "    if (BACKGROUND_COLOR)\n",
              "      GL.clearColor(BACKGROUND_COLOR[0], \n",
              "                    BACKGROUND_COLOR[1], \n",
              "                    BACKGROUND_COLOR[2], \n",
              "                    1.0);\n",
              "    else\n",
              "      GL.clearColor(0.2, 0.2, 0.2, 1.0);\n",
              "    GL.enable(GL.DEPTH_TEST);\n",
              "\n",
              "    var shader_program;\n",
              "    if (DIMENSION == 2)\n",
              "      shader_program = initialize_shader(\n",
              "          GL, VERTEX_SHADER_SOURCE_2D, FRAGMENT_SHADER_SOURCE_2D);\n",
              "    else if (DIMENSION == 3)\n",
              "      shader_program = initialize_shader(\n",
              "          GL, VERTEX_SHADER_SOURCE_3D, FRAGMENT_SHADER_SOURCE_3D);\n",
              "\n",
              "    SHADER = {\n",
              "      program: shader_program,\n",
              "      attribute: {\n",
              "          vertex_position: GL.getAttribLocation(shader_program, 'vertex_position'),\n",
              "          position: GL.getAttribLocation(shader_program, 'position'),\n",
              "          size: GL.getAttribLocation(shader_program, 'size'),\n",
              "          color: GL.getAttribLocation(shader_program, 'color'),\n",
              "      },\n",
              "      uniform: {\n",
              "          color: GL.getUniformLocation(shader_program, 'color'),\n",
              "          global_size: GL.getUniformLocation(shader_program, 'global_size'),\n",
              "          use_global_size: GL.getUniformLocation(shader_program, 'use_global_size'),\n",
              "          global_color: GL.getUniformLocation(shader_program, 'global_color'),\n",
              "          use_global_color: GL.getUniformLocation(shader_program, 'use_global_color'),\n",
              "          use_position: GL.getUniformLocation(shader_program, 'use_position')\n",
              "      },\n",
              "    };\n",
              "\n",
              "    if (DIMENSION == 2) {\n",
              "      SHADER.uniform['screen_position'] = GL.getUniformLocation(shader_program, 'screen_position');\n",
              "      SHADER.uniform['screen_size'] = GL.getUniformLocation(shader_program, 'screen_size');\n",
              "    } else if (DIMENSION == 3) {\n",
              "      SHADER.attribute['vertex_normal'] = GL.getAttribLocation(shader_program, 'vertex_normal');\n",
              "      SHADER.uniform['perspective'] = GL.getUniformLocation(shader_program, 'perspective');\n",
              "      SHADER.uniform['light_direction'] = GL.getUniformLocation(shader_program, 'light_direction');\n",
              "    }\n",
              "\n",
              "    GL.useProgram(shader_program);\n",
              "    \n",
              "    GL.uniform4f(SHADER.uniform.color, 0.9, 0.9, 1.0, 1.0);\n",
              "    GL.uniform1f(SHADER.uniform.global_size, 1.0);\n",
              "    GL.uniform1i(SHADER.uniform.use_global_size, true);\n",
              "\n",
              "    GL.uniform3f(SHADER.uniform.global_color, 1.0, 1.0, 1.0);\n",
              "    GL.uniform1i(SHADER.uniform.use_global_color, true);\n",
              "    GL.uniform1f(SHADER.uniform.use_position, 1.0);\n",
              "\n",
              "    var inorm = 1.0 / Math.sqrt(3);\n",
              "    GL.uniform3f(SHADER.uniform.light_direction, inorm, -inorm, inorm)\n",
              "\n",
              "    SHAPE['Disk'] = make_disk(GL, SHADER, 16, 0.5);\n",
              "    SHAPE['Sphere'] = make_sphere(GL, SHADER, 16, 16, 0.5);\n",
              "\n",
              "    const vao = GL.createVertexArray();\n",
              "    GL.bindVertexArray(vao);\n",
              "  }\n",
              "\n",
              "  function make_disk(gl, shader, segments, radius) {\n",
              "    var position = new Float32Array(segments * DIMENSION * 3);\n",
              "    for (var s = 0 ; s < segments ; s++) {\n",
              "        const th = 2 * s / segments * Math.PI;\n",
              "        const th_p = 2 * (s + 1) / segments * Math.PI;\n",
              "        position.set([0.0, 0.0], s * 3 * DIMENSION);\n",
              "        position.set([radius * Math.cos(th), radius * Math.sin(th)],\n",
              "                     s * 3 * DIMENSION + DIMENSION);\n",
              "        position.set([radius * Math.cos(th_p), radius * Math.sin(th_p)], \n",
              "                     s * 3 * DIMENSION + 2 * DIMENSION);\n",
              "    }\n",
              "\n",
              "    var buffer = gl.createBuffer();\n",
              "    gl.bindBuffer(gl.ARRAY_BUFFER, buffer);\n",
              "    gl.bufferData(gl.ARRAY_BUFFER, position, gl.STATIC_DRAW);\n",
              "\n",
              "    return {\n",
              "      vertex_position: position,\n",
              "      vertex_buffer: buffer,\n",
              "      vertex_count: segments * 3,\n",
              "    };\n",
              "  }\n",
              "\n",
              "  function make_sphere(gl, shader, horizontal_segments, vertical_segments, radius) {\n",
              "    const stride = DIMENSION * 3 * 2;  // 3 vertices per tri, two tris per quad.\n",
              "    if (DIMENSION != 3) {\n",
              "      return null;\n",
              "      // Error Checking.\n",
              "    }\n",
              "\n",
              "    var position = new Float32Array(vertical_segments * horizontal_segments * stride);\n",
              "    var normal = new Float32Array(vertical_segments * horizontal_segments * stride);\n",
              "\n",
              "    var dtheta = 2 * Math.PI / horizontal_segments;\n",
              "    var dphi = Math.PI / vertical_segments;\n",
              "\n",
              "    for (var vs = 0 ; vs < vertical_segments ; vs++) {\n",
              "      const phi_0 = vs * dphi;\n",
              "      const phi_1 = (vs + 1) * dphi;\n",
              "      const offset = vs * horizontal_segments * stride;\n",
              "      for (var hs = 0 ; hs < horizontal_segments ; hs++) {\n",
              "        const theta_0 = hs * dtheta;\n",
              "        const theta_1 = (hs + 1) * dtheta;\n",
              "\n",
              "        const x0 = radius * Math.sin(phi_0) * Math.cos(theta_0);\n",
              "        const y0 = radius * Math.sin(phi_0) * Math.sin(theta_0);\n",
              "        const z0 = radius * Math.cos(phi_0);\n",
              "\n",
              "        const x1 = radius * Math.sin(phi_1) * Math.cos(theta_0);\n",
              "        const y1 = radius * Math.sin(phi_1) * Math.sin(theta_0);\n",
              "        const z1 = radius * Math.cos(phi_1);\n",
              "\n",
              "        const x2 = radius * Math.sin(phi_0) * Math.cos(theta_1);\n",
              "        const y2 = radius * Math.sin(phi_0) * Math.sin(theta_1);\n",
              "        const z2 = radius * Math.cos(phi_0);\n",
              "\n",
              "        const x3 = radius * Math.sin(phi_1) * Math.cos(theta_1);\n",
              "        const y3 = radius * Math.sin(phi_1) * Math.sin(theta_1);\n",
              "        const z3 = radius * Math.cos(phi_1);\n",
              "\n",
              "        position.set([x0, y0, z0,\n",
              "                      x1, y1, z1,\n",
              "                      x2, y2, z2,\n",
              "                      x1, y1, z1,\n",
              "                      x3, y3, z3,\n",
              "                      x2, y2, z2], offset + hs * stride);\n",
              "\n",
              "        normal.set([x0 / radius, y0 / radius, z0 / radius,\n",
              "                    x1 / radius, y1 / radius, z1 / radius,\n",
              "                    x2 / radius, y2 / radius, z2 / radius,\n",
              "                    x1 / radius, y1 / radius, z1 / radius,\n",
              "                    x3 / radius, y3 / radius, z3 / radius,\n",
              "                    x2 / radius, y2 / radius, z2 / radius], offset + hs * stride);              \n",
              "      }\n",
              "    }\n",
              "\n",
              "    var buffer = gl.createBuffer();\n",
              "    gl.bindBuffer(gl.ARRAY_BUFFER, buffer);\n",
              "    gl.bufferData(gl.ARRAY_BUFFER, position, gl.STATIC_DRAW);\n",
              "\n",
              "    var normal_buffer = gl.createBuffer();\n",
              "    gl.bindBuffer(gl.ARRAY_BUFFER, normal_buffer);\n",
              "    gl.bufferData(gl.ARRAY_BUFFER, normal, gl.STATIC_DRAW);\n",
              "\n",
              "    return {\n",
              "      vertex_position: position,\n",
              "      vertex_buffer: buffer,\n",
              "      vertex_normals: normal,\n",
              "      vertex_normal_buffer: normal_buffer,\n",
              "      vertex_count: vertical_segments * horizontal_segments * 3 * 2\n",
              "    };\n",
              "  }\n",
              "\n",
              "  function set_attribute(geometry, name) {\n",
              "    if (!geometry[name]) {\n",
              "      if (SIZE[name] == 1)\n",
              "        GL.uniform1f(SHADER.uniform['global_' + name], 1.0);\n",
              "      else if (SIZE[name] == 2)\n",
              "        GL.uniform2f(SHADER.uniform['global_' + name], 1.0, 1.0);\n",
              "      else if (SIZE[name] == 3)\n",
              "        GL.uniform3f(SHADER.uniform['global_' + name], 1.0, 1.0, 1.0);\n",
              "\n",
              "      GL.uniform1i(SHADER.uniform['use_global_' + name], true);\n",
              "    } else if (geometry[name + '_type'] == 'GLOBAL') {\n",
              "      if (SIZE[name] == 1)\n",
              "        GL.uniform1fv(SHADER.uniform['global_' + name], geometry[name]);\n",
              "      else if (SIZE[name] == 2)\n",
              "        GL.uniform2fv(SHADER.uniform['global_' + name], geometry[name]);\n",
              "      else if (SIZE[name] == 3)\n",
              "        GL.uniform3fv(SHADER.uniform['global_' + name], geometry[name]);\n",
              "\n",
              "      GL.uniform1i(SHADER.uniform['use_global_' + name], true);\n",
              "    } else {\n",
              "      GL.enableVertexAttribArray(SHADER.attribute[name]);\n",
              "      var stride = SIZE[name] * geometry.count;\n",
              "      GL.bindBuffer(GL.ARRAY_BUFFER, geometry[name + '_buffer']);\n",
              "      if (geometry[name + '_type'] == GL.DYNAMIC_DRAW) {\n",
              "        const data = geometry[name].slice(FRAME_COUNT * stride, \n",
              "                                          (FRAME_COUNT + 1) * stride);\n",
              "        GL.bufferSubData(GL.ARRAY_BUFFER, 0, data);\n",
              "      }\n",
              "      GL.vertexAttribPointer(\n",
              "        SHADER.attribute[name],               \n",
              "        SIZE[name],        \n",
              "        GL.FLOAT,         \n",
              "        false,            \n",
              "        0,    \n",
              "        0\n",
              "      );                \n",
              "      GL.vertexAttribDivisor(SHADER.attribute[name], 1);\n",
              "\n",
              "      GL.uniform1i(SHADER.uniform['use_global_' + name], false);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  var loops = 0;\n",
              "\n",
              "  function update_frame() {\n",
              "    if(!GL) {\n",
              "      window.requestAnimationFrame(update_frame);\n",
              "      return;\n",
              "    }\n",
              "\n",
              "    GL.clear(GL.COLOR_BUFFER_BIT | GL.DEPTH_BUFFER_BIT);\n",
              "    \n",
              "    if (!IS_LOADED) {\n",
              "      window.requestAnimationFrame(update_frame);\n",
              "      return;\n",
              "    }\n",
              "\n",
              "    if (DIMENSION == 2) {\n",
              "      var camera_x = SCREEN_POSITION[0];\n",
              "      var camera_y = SCREEN_POSITION[1];\n",
              "\n",
              "      if (DRAGGING) {\n",
              "        const delta = get_drag_offset();\n",
              "        camera_x += delta[0];\n",
              "        camera_y += delta[1];\n",
              "      }\n",
              "      GL.uniform2f(SHADER.uniform.screen_position, camera_x, camera_y);\n",
              "      GL.uniform2f(SHADER.uniform.screen_size, CAMERA_SIZE[0], CAMERA_SIZE[1]);\n",
              "    } else if (DIMENSION == 3) {\n",
              "\n",
              "      // Now these are some janky globals.\n",
              "      if (DRAGGING) {\n",
              "        var yaw = YAW;\n",
              "        var pitch = PITCH;\n",
              "        const delta = get_drag_offset();\n",
              "        YAW = YAW - delta[0];\n",
              "        PITCH = PITCH - delta[1];\n",
              "        make_look_at();\n",
              "        YAW = yaw;\n",
              "        PITCH = pitch;\n",
              "      }\n",
              "\n",
              "      GL.uniformMatrix4fv(SHADER.uniform.perspective, false,\n",
              "                          mat4.multiply(EYE, PERSPECTIVE, LOOK_AT));\n",
              "    }\n",
              "\n",
              "    if (CURRENT_FRAME >= FRAME_COUNT - 1) {\n",
              "      loops++;\n",
              "      CURRENT_FRAME = 0;\n",
              "    }\n",
              "\n",
              "    for (var name in GEOMETRY) {\n",
              "      var geom = GEOMETRY[name];\n",
              "\n",
              "      set_attribute(geom, 'size');\n",
              "      set_attribute(geom, 'color');\n",
              "\n",
              "      var shape = geom.shape;\n",
              "      var vertex_buffer;\n",
              "      var vertex_count;\n",
              "      var vertex_normal_buffer = null;\n",
              "\n",
              "      if (shape != 'Bond') {\n",
              "        shape = SHAPE[shape];\n",
              "\n",
              "        update_shape(geom);        \n",
              "\n",
              "        vertex_buffer = shape.vertex_buffer;\n",
              "        vertex_count = shape.vertex_count;\n",
              "        vertex_normal_buffer = shape.vertex_normal_buffer;\n",
              "      } else {\n",
              "        vertex_count = update_bond_vertex_data(GEOMETRY[geom.reference_geometry],\n",
              "                                               geom);\n",
              "        vertex_buffer = geom.vertex_buffer;\n",
              "        vertex_normal_buffer = geom.vertex_normal_buffer;\n",
              "      }\n",
              "\n",
              "      GL.enableVertexAttribArray(SHADER.attribute.vertex_position);\n",
              "      GL.bindBuffer(GL.ARRAY_BUFFER, vertex_buffer);\n",
              "      GL.vertexAttribPointer(\n",
              "        SHADER.attribute.vertex_position,\n",
              "        DIMENSION,\n",
              "        GL.FLOAT,\n",
              "        false,\n",
              "        0,\n",
              "        0\n",
              "      );\n",
              "\n",
              "      if (DIMENSION == 3 && vertex_normal_buffer) { \n",
              "        GL.enableVertexAttribArray(SHADER.attribute.vertex_normal);\n",
              "        GL.bindBuffer(GL.ARRAY_BUFFER, vertex_normal_buffer);\n",
              "        GL.vertexAttribPointer(\n",
              "          SHADER.attribute.vertex_normal,\n",
              "          DIMENSION,\n",
              "          GL.FLOAT,\n",
              "          false,\n",
              "          0,\n",
              "          0\n",
              "        );\n",
              "      }\n",
              "\n",
              "      if (shape == 'Bond')\n",
              "      {\n",
              "        GL.drawArrays(GL.TRIANGLES, 0, vertex_count);\n",
              "      }\n",
              "      else {\n",
              "        GL.drawArraysInstanced(GL.TRIANGLES, 0, vertex_count, geom.count);\n",
              "      }\n",
              "    }\n",
              "\n",
              "    if(IS_PLAYING) {\n",
              "      CURRENT_FRAME++;\n",
              "      FRAME_RANGE.value = CURRENT_FRAME;\n",
              "    }\n",
              "\n",
              "    window.requestAnimationFrame(update_frame);\n",
              "  }\n",
              "\n",
              "  function update_shape(geometry) {\n",
              "    GL.enableVertexAttribArray(SHADER.attribute.position);\n",
              "    var stride = geometry.count * DIMENSION;\n",
              "    GL.bindBuffer(GL.ARRAY_BUFFER, geometry.position_buffer);\n",
              "    if (geometry.position_type == GL.DYNAMIC_DRAW) {\n",
              "      const positions = geometry.position.subarray(CURRENT_FRAME * stride, \n",
              "                                                   (CURRENT_FRAME + 1) * stride);\n",
              "      GL.bufferSubData(GL.ARRAY_BUFFER, 0, positions);\n",
              "    }\n",
              "    GL.vertexAttribPointer(\n",
              "      SHADER.attribute.position,               \n",
              "      DIMENSION,        \n",
              "      GL.FLOAT,         \n",
              "      false,            \n",
              "      0,    \n",
              "      0\n",
              "    );                \n",
              "    GL.vertexAttribDivisor(SHADER.attribute.position, 1);\n",
              "    GL.uniform1f(SHADER.uniform.use_position, 1.0);\n",
              "  }\n",
              "\n",
              "  function update_bond_vertex_data(reference_geometry, bonds) {\n",
              "    const geom = reference_geometry;\n",
              "    const N = geom.count;\n",
              "    var stride = N * DIMENSION;\n",
              "    const positions = geom.position.subarray(CURRENT_FRAME * stride, \n",
              "                                             (CURRENT_FRAME + 1) * stride);\n",
              "    const neighbors = bonds.max_neighbors;\n",
              "\n",
              "    var vertex_count = 0;\n",
              "    var vertices = bonds.vertices;\n",
              "    var normals = bonds.normals;\n",
              "\n",
              "    for (var i = 0 ; i < N ; i++) {\n",
              "      var r_i = positions.subarray(i * DIMENSION, (i + 1) * DIMENSION);\n",
              "      for (var j = 0 ; j < neighbors ; j++) {\n",
              "        const idx = i * neighbors + j; \n",
              "        const nbr_idx = Math.round(bonds.neighbor_idx[idx]);\n",
              "\n",
              "        if (nbr_idx < i) {\n",
              "          var r_j = positions.subarray(nbr_idx * DIMENSION, (nbr_idx + 1) * DIMENSION);\n",
              "          vertex_count = push_bond(vertices, normals, vertex_count, r_i, r_j, 0.1); //bonds.diameter / 2.0);\n",
              "        }\n",
              "      }\n",
              "    }\n",
              "\n",
              "    GL.bindBuffer(GL.ARRAY_BUFFER, bonds.vertex_buffer);\n",
              "    GL.bufferData(GL.ARRAY_BUFFER, vertices, GL.DYNAMIC_DRAW);\n",
              "\n",
              "    GL.bindBuffer(GL.ARRAY_BUFFER, bonds.vertex_normal_buffer);\n",
              "    GL.bufferData(GL.ARRAY_BUFFER, normals, GL.DYNAMIC_DRAW);\n",
              "\n",
              "    GL.uniform1f(SHADER.uniform.use_position, 0.0);\n",
              "    GL.uniform1i(SHADER.uniform.use_global_size, 1);\n",
              "    GL.uniform1i(SHADER.uniform.use_global_color, 1);\n",
              "\n",
              "    return vertex_count;\n",
              "  }\n",
              "\n",
              "  BOND_C_TABLE = [];\n",
              "  BOND_S_TABLE = [];\n",
              "  for (var i = 0 ; i < BOND_SEGMENTS ; i++)\n",
              "  {\n",
              "    BOND_C_TABLE.push(Math.cos(2 * i * Math.PI / BOND_SEGMENTS));\n",
              "    BOND_S_TABLE.push(Math.sin(2 * i * Math.PI / BOND_SEGMENTS));\n",
              "  }\n",
              "\n",
              "  function push_bond(vertices, normals, vertex_count, r_i, r_j, radius) {\n",
              "    var dr = vec3.fromValues(r_i[0] - r_j[0], \n",
              "                             r_i[1] - r_j[1], \n",
              "                             r_i[2] - r_j[2]);\n",
              "\n",
              "    if (Math.abs(dr[0]) > BOX_SIZE / 2.0 || \n",
              "        Math.abs(dr[1]) > BOX_SIZE / 2.0 ||\n",
              "        Math.abs(dr[2]) > BOX_SIZE / 2.0 )\n",
              "      return vertex_count;\n",
              "\n",
              "    var up = vec3.fromValues(0.0, 1.0, 0.0);\n",
              "    var left = vec3.fromValues(0.0, 1.0, 0.0);\n",
              "\n",
              "    vec3.cross(left, up, dr);\n",
              "    vec3.normalize(left, left);\n",
              "\n",
              "    vec3.cross(up, left, dr);\n",
              "    vec3.normalize(up, up);\n",
              "\n",
              "    var normal = vec3.fromValues(0.0, 0.0, 0.0);\n",
              " \n",
              "    for (var i = 0 ; i < BOND_SEGMENTS ; i++) {\n",
              "      const c1 = radius * BOND_C_TABLE[i];\n",
              "      const c2 = radius * BOND_C_TABLE[(i + 1) % BOND_SEGMENTS];\n",
              "      const s1 = radius * BOND_S_TABLE[i];\n",
              "      const s2 = radius * BOND_S_TABLE[(i + 1) % BOND_SEGMENTS];\n",
              "\n",
              "      vertices.set([\n",
              "        r_j[0] + left[0] * c1 + up[0] * s1,\n",
              "        r_j[1] + left[1] * c1 + up[1] * s1,\n",
              "        r_j[2] + left[2] * c1 + up[2] * s1,\n",
              "\n",
              "        r_i[0] + left[0] * c1 + up[0] * s1,\n",
              "        r_i[1] + left[1] * c1 + up[1] * s1,\n",
              "        r_i[2] + left[2] * c1 + up[2] * s1,\n",
              "\n",
              "        r_j[0] + left[0] * c2 + up[0] * s2,\n",
              "        r_j[1] + left[1] * c2 + up[1] * s2,\n",
              "        r_j[2] + left[2] * c2 + up[2] * s2,\n",
              "\n",
              "        r_i[0] + left[0] * c1 + up[0] * s1,\n",
              "        r_i[1] + left[1] * c1 + up[1] * s1,\n",
              "        r_i[2] + left[2] * c1 + up[2] * s1,\n",
              "\n",
              "        r_i[0] + left[0] * c2 + up[0] * s2,\n",
              "        r_i[1] + left[1] * c2 + up[1] * s2,\n",
              "        r_i[2] + left[2] * c2 + up[2] * s2,\n",
              "\n",
              "        r_j[0] + left[0] * c2 + up[0] * s2,\n",
              "        r_j[1] + left[1] * c2 + up[1] * s2,\n",
              "        r_j[2] + left[2] * c2 + up[2] * s2,        \n",
              "      ], 3 * (vertex_count + 6 * i));\n",
              "\n",
              "      vec3.cross(normal, \n",
              "                 [r_j[0] - r_i[0] + left[0] * c1 + up[0] * s1, \n",
              "                  r_j[1] - r_i[1] + left[1] * c1 + up[1] * s1, \n",
              "                  r_j[2] - r_i[2] + left[2] * c1 + up[2] * s1],\n",
              "                 [left[0] * (c1 - c2) + up[0] * (s1 - s2), \n",
              "                  left[1] * (c1 - c2) + up[1] * (s1 - s2), \n",
              "                  left[2] * (c1 - c2) + up[2] * (s1 - s2)]);\n",
              "      vec3.normalize(normal, normal);\n",
              "\n",
              "      normals.set([\n",
              "        normal[0], normal[1], normal[2],\n",
              "        normal[0], normal[1], normal[2],\n",
              "        normal[0], normal[1], normal[2],\n",
              "        normal[0], normal[1], normal[2],\n",
              "        normal[0], normal[1], normal[2],\n",
              "        normal[0], normal[1], normal[2],\n",
              "      ], 3 * (vertex_count + 6 * i));\n",
              "    }\n",
              "    return vertex_count + 6 * BOND_SEGMENTS;\n",
              "  }\n",
              "\n",
              "  // SHADER CODE\n",
              "\n",
              "  const VERTEX_SHADER_SOURCE_2D = `#version 300 es\n",
              "    // Vertex Shader Program.\n",
              "    in vec2 vertex_position;\n",
              "    in vec2 position;\n",
              "    in float size;\n",
              "    in vec3 color;\n",
              "\n",
              "    out vec4 v_color;\n",
              "\n",
              "    uniform float use_position;\n",
              "\n",
              "    uniform vec2 screen_position;\n",
              "    uniform vec2 screen_size;\n",
              "\n",
              "    uniform float global_size;\n",
              "    uniform bool use_global_size;\n",
              "\n",
              "    uniform vec3 global_color;\n",
              "    uniform bool use_global_color;\n",
              "\n",
              "    void main() {\n",
              "      float _size = use_global_size ? global_size : size;\n",
              "      vec2 v = (_size * vertex_position + position - screen_position) / screen_size;\n",
              "      gl_Position = vec4(v, 0.0, 1.0);\n",
              "      v_color = vec4(use_global_color ? global_color : color, 1.0f);\n",
              "    }\n",
              "  `;\n",
              "\n",
              "  const FRAGMENT_SHADER_SOURCE_2D = `#version 300 es\n",
              "    precision mediump float;\n",
              "\n",
              "    in vec4 v_color;\n",
              "\n",
              "    out vec4 outColor;\n",
              "\n",
              "    void main() {\n",
              "      outColor = v_color;\n",
              "    }\n",
              "  `;\n",
              "\n",
              "   const VERTEX_SHADER_SOURCE_3D = `#version 300 es\n",
              "    // Vertex Shader Program.\n",
              "    in vec3 vertex_position;\n",
              "    in vec3 vertex_normal;\n",
              "\n",
              "    in vec3 position;\n",
              "    in float size;\n",
              "    in vec3 color;\n",
              "\n",
              "    out vec4 v_color;\n",
              "    out vec3 v_normal;\n",
              "\n",
              "    uniform mat4 perspective;\n",
              "\n",
              "    uniform float use_position;\n",
              "\n",
              "    uniform float global_size;\n",
              "    uniform bool use_global_size;\n",
              "\n",
              "    uniform vec3 global_color;\n",
              "    uniform bool use_global_color;\n",
              "\n",
              "    void main() {\n",
              "      vec3 pos = use_position * position;\n",
              "      float _size = use_global_size ? global_size : size;\n",
              "\n",
              "      vec3 v = (_size * vertex_position + pos);\n",
              "      gl_Position = perspective * vec4(v, 1.0);\n",
              "\n",
              "      v_color = vec4(use_global_color ? global_color : color, 1.0f);\n",
              "      v_normal = vertex_normal;\n",
              "    }\n",
              "  `;\n",
              "\n",
              "  const FRAGMENT_SHADER_SOURCE_3D = `#version 300 es\n",
              "    precision mediump float;\n",
              "\n",
              "    in vec4 v_color;\n",
              "    in vec3 v_normal;\n",
              "\n",
              "    uniform vec3 light_direction;\n",
              "\n",
              "    out vec4 outColor;\n",
              "\n",
              "    void main() {\n",
              "      float diffuse_magnitude = clamp(-dot(v_normal, light_direction), 0.0, 1.0) + 0.2;\n",
              "\n",
              "      outColor = vec4(vec3(v_color) * diffuse_magnitude, v_color.a);\n",
              "    }\n",
              "  `;\n",
              "\n",
              "  function initialize_shader(gl, vertex_shader_source, fragment_shader_source) {\n",
              "\n",
              "    const vertex_shader = compile_shader(\n",
              "      gl, gl.VERTEX_SHADER, vertex_shader_source);\n",
              "    const fragment_shader = compile_shader(\n",
              "      gl, gl.FRAGMENT_SHADER, fragment_shader_source);\n",
              "\n",
              "    const shader_program = gl.createProgram();\n",
              "    gl.attachShader(shader_program, vertex_shader);\n",
              "    gl.attachShader(shader_program, fragment_shader);\n",
              "    gl.linkProgram(shader_program);\n",
              "\n",
              "    if (!gl.getProgramParameter(shader_program, gl.LINK_STATUS)) {\n",
              "      alert(\n",
              "        'Unable to initialize shader program: ' + \n",
              "        gl.getProgramInfoLog(shader_program)\n",
              "        );\n",
              "        return null;\n",
              "    }\n",
              "    return shader_program;\n",
              "  }\n",
              "\n",
              "  function compile_shader(gl, type, source) {\n",
              "    const shader = gl.createShader(type);\n",
              "    gl.shaderSource(shader, source);\n",
              "    gl.compileShader(shader);\n",
              "\n",
              "    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n",
              "      alert('An error occured compiling shader: ' + gl.getShaderInfoLog(shader));\n",
              "      gl.deleteShader(shader);\n",
              "      return null;\n",
              "    }\n",
              "\n",
              "    return shader;\n",
              "  }\n",
              "\n",
              "  // UI\n",
              "\n",
              "  var DRAG_START;\n",
              "  var DRAG_CURRENT;\n",
              "  var DRAGGING = false;\n",
              "\n",
              "  CANVAS.addEventListener('mousedown', function(e) {\n",
              "    DRAG_START = [e.offsetX, e.offsetY];\n",
              "    DRAGGING = true;\n",
              "  });\n",
              "\n",
              "  CANVAS.addEventListener('mousemove', function(e) {\n",
              "    DRAG_CURRENT = [e.offsetX, e.offsetY];\n",
              "  });\n",
              "\n",
              "  CANVAS.addEventListener('mouseup', function(e) {\n",
              "    const delta = get_drag_offset();\n",
              "    if (DIMENSION == 2) {\n",
              "      SCREEN_POSITION = [SCREEN_POSITION[0] + delta[0],\n",
              "                         SCREEN_POSITION[1] + delta[1]];\n",
              "    } else if (DIMENSION == 3) {\n",
              "      YAW -= delta[0];\n",
              "      PITCH -= delta[1];\n",
              "\n",
              "      if (PITCH > Math.PI / 2.1)\n",
              "        PITCH = Math.PI / 2.1;\n",
              "      if (PITCH < -Math.PI / 2.1)\n",
              "        PITCH = -Math.PI / 2.1;\n",
              "\n",
              "      make_look_at();\n",
              "    }\n",
              "\n",
              "    DRAGGING = false;\n",
              "  });\n",
              "\n",
              "  function toggle_play() {\n",
              "    IS_PLAYING = !IS_PLAYING;\n",
              "    console.log(PLAY_PAUSE_BUTTON);\n",
              "    if(IS_PLAYING)\n",
              "      PLAY_PAUSE_BUTTON.innerHTML = '||';\n",
              "    else\n",
              "      PLAY_PAUSE_BUTTON.innerHTML = '>';\n",
              "  }\n",
              "\n",
              "  function change_frame(value) {\n",
              "    if (!IS_LOADED)\n",
              "      return;\n",
              "    CURRENT_FRAME = value;\n",
              "    FRAME_RANGE.innerHTML = value;\n",
              "  }\n",
              "\n",
              "  function get_drag_offset() {\n",
              "    var delta = [DRAG_START[0] - DRAG_CURRENT[0],\n",
              "                 -DRAG_START[1] + DRAG_CURRENT[1]];\n",
              "    delta = [delta[0] / canvas.width * 2, delta[1] / canvas.height * 2];\n",
              "    if (DIMENSION == 2) {\n",
              "      delta = [delta[0] * CAMERA_SIZE[0],\n",
              "               delta[1] * CAMERA_SIZE[1]];\n",
              "    }\n",
              "    return delta;\n",
              "  }\n",
              "\n",
              "  const SCALE_SPEED = 0.1;\n",
              "  CANVAS.addEventListener('mousewheel', function(e) {\n",
              "    var delta = Math.sign(e.wheelDeltaY);\n",
              "    if (navigator.appVersion.indexOf('Mac'))\n",
              "      delta *= -0.1;\n",
              "    if (DIMENSION == 2) {\n",
              "      CAMERA_SIZE[0] = CAMERA_SIZE[0] * (1 + delta * SCALE_SPEED);\n",
              "      CAMERA_SIZE[1] = CAMERA_SIZE[1] * (1 + delta * SCALE_SPEED);\n",
              "    } else if (DIMENSION == 3) {\n",
              "      VIEW_DISTANCE = VIEW_DISTANCE * (1 + delta * SCALE_SPEED);\n",
              "      make_look_at();\n",
              "    }\n",
              "    e.preventDefault();\n",
              "  }, false);\n",
              "  CANVAS.addEventListener('DOMMouseScroll', function(e) {\n",
              "    const delta = Math.sign(e.detail);\n",
              "    if (DIMENSION == 2) {\n",
              "      CAMERA_SIZE[0] = CAMERA_SIZE[0] * (1 + delta * SCALE_SPEED);\n",
              "      CAMERA_SIZE[1] = CAMERA_SIZE[1] * (1 + delta * SCALE_SPEED);\n",
              "    } else if (DIMENSION == 3) {\n",
              "      VIEW_DISTANCE = VIEW_DISTANCE * (1 + delta * SCALE_SPEED);\n",
              "      make_look_at();\n",
              "    }\n",
              "    e.preventDefault();\n",
              "  }, false);\n",
              "\n",
              "\n",
              "  // SERIALIZATION UTILITIES\n",
              "  function decode(sBase64, nBlocksSize) {\n",
              "    var chrs = atob(sBase64);\n",
              "    var array = new Uint8Array(new ArrayBuffer(chrs.length));\n",
              "\n",
              "    for(var i = 0 ; i < chrs.length ; i++) {\n",
              "      array[i] = chrs.charCodeAt(i);\n",
              "    }\n",
              "\n",
              "    return new Float32Array(array.buffer);\n",
              "  }\n",
              "\n",
              "  function from_json(data) { \n",
              "    data = data.data['application/json'];\n",
              "\n",
              "    if (typeof data == 'string') {\n",
              "      return JSON.parse(data);\n",
              "    }\n",
              "\n",
              "    return data;\n",
              "  }\n",
              "\n",
              "  // RUN CELL\n",
              "\n",
              "  load_simulation();\n",
              "  update_frame();\n",
              "</script>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "khxnjOIbNS9P"
      },
      "source": [
        "Finally, let's plot the energy trajectory that we observer during FIRE minimization."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "paMpEkUUWm9c",
        "outputId": "0e79ec43-328f-4ef6-89cc-295d878cf6ce",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        }
      },
      "source": [
        "plt.plot(E, linewidth=3)\n",
        "\n",
        "format_plot('step', '$E$')\n",
        "finalize_plot()"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}